Comments (5)
Ah interesting, I hit this same error when trying to use llama2-lora. I found if I disabled the "best-effort sharding" in hf_checkpoints I could get training to work:
levanter/src/levanter/compat/hf_checkpoints.py
Line 1072 in 9adba01
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ok i think can be fixed with a long-standing thing I've been meaning to fix in Haliax (but isn't quite compatible with some of the CPU-only testing I do)
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can you try #622, which is a simpler fix than the haliax thing
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Well that's a remarkably unhelpful error message. I have a strong suspicion it's because of #588 and it's now using an incompatible mesh. Can you try reverting that commit and seeing if that fixes? If it fixes, it's a pretty easy patch
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Indeed. I just checked out 2bb1252 and it trains nicely, but I had to reduce parallelism to 8 to make it fit into the v4-64, strange.
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Related Issues (20)
- Add requirements.txt (poetry toml) for tests
- Double BOS token on Mistral HOT 2
- Training job hangs after saving checkpoint due to curl timeout error HOT 1
- Silent failure at the data tokenization pipeline due to duplicate file names HOT 1
- Hang when training LLama7B on TPU v5e-16 HOT 9
- Issues with Splash Attention HOT 9
- HF exported models are always float32 HOT 1
- Make Llama be the default architecture/test case/example
- Detect use of an invalid tokenizer cache HOT 6
- Fix Sophia-H when using Splash Attention
- gemma config on hf switched to "gelu" instead of "gelu_pytorch_tanh" for some reason HOT 1
- Instant Data loader resumes
- Random thoughts on the new docker stuff HOT 15
- Launch script multislice HOT 6
- Sharding error when trying to serialize PEFT models HOT 19
- My bot
- Change launch.py to not rebuild docker container on TPU node failure (with retries)
- Sigma
- preemptible in config wasn't registered as capacity_type
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